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Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.
Motivated by the high interest in developing with LLMs, we have created this new prompt engineering guide that contains all the latest papers, learning guides, lectures, references, and tools related to prompt engineering for LLMs.
🌐 Prompt Engineering Guide (Web Version)
🎉 We are excited to launch our brand new prompt engineering courses under the DAIR.AI Academy. Join Now!
Happy Prompting!
You can also find the most up-to-date guides on our new website https://www.promptingguide.ai/.
We have published a 1 hour lecture that provides a comprehensive overview of prompting techniques, applications, and tools.
To run the guide locally, for example to check the correct implementation of a new translation, you will need to:
pnpm
if not present in your system. Check here for detailed instructions.pnpm i next react react-dom nextra nextra-theme-docs
pnpm dev
http://localhost:3000/
Some places where we have been featured:
If you are using the guide for your work or research, please cite us as follows:
@article{Saravia_Prompt_Engineering_Guide_2022,
author = {Saravia, Elvis},
journal = {https://github.com/dair-ai/Prompt-Engineering-Guide},
month = {12},
title = {{Prompt Engineering Guide}},
year = {2022}
}
Feel free to open a PR if you think something is missing here. Always welcome feedback and suggestions. Just open an issue!